This study presents a year-round automated electrical resistivity tomography monitoring of a steep permafrost rockwall combined with borehole temperature, anchor load and piezometer observations. The joint analysis revealed seasonal phases with enhanced mechanical forcing of rockwalls related to high hydrostatic and cryostatic pressures, which are of particular interest for understanding preconditioning of rock instabilities.

We studied how streams and sediment systems along Namibia’s Skeleton Coast link inland sources with coastal plains where sediments are deposited. Using statistical tools, we identified distinct groups of systems with varying connection strengths. Fan gradient proved more important than climate or rock type, helping to assess how desert landscapes record past environmental change over time.

Climate change increases landslide risk in cold regions. We analyzed 12 years of GPS, borehole, water, and seismic data from two landslides in Arctic Norway, one with permafrost and one without. Both accelerate in spring and autumn due to water infiltration. One slip zone shows increasing snowmelt sensitivity while seismic data reveal seasonal stiffness changes. Results advance understanding of water-driven landslide dynamics in Arctic climates.

Studying peatland dynamics over long timescales requires a proxy for past peat cover. In this paper, we explore using cosmogenic nuclides to infer peat thicknesses averaged over 100 kyr timescales. We find that long-term peat thicknesses inferred from cosmogenic nuclides at an upland peatland site in the Belgian Ardennes are consistent with independent constraints, but exceed modern peat thicknesses. We attribute this discrepancy to peat degradation associated with historical land use.

Slow-moving landslides respond to seasonal climate variations, but displacement time series from optical satellite imagery often contain illumination and shadow related biases that obscure true signals. This study assesses methods to mitigate these errors and reveals kinematic changes and controlling factors of a large slow-moving landslide in the Argentinean Andes.

This study shows dune mobility can be predicted using a simple statistical method based only on meteorological data from nearby weather stations and freely available climate indices. The model provides an accessible, low-cost way to anticipate future dune behavior. This information is highly valuable for local communities and decision-makers, as it supports better land-use planning and helps reduce potential damage caused by dune migration, contributing to the management of coastal environments.

Water level suddenly rises during flash floods in dry regions having a distinct impact on bedload – large sediment rolling and saltating on the riverbed. Using sensor-equipped pebbles and seismic monitoring in a field setting, we demonstrate that bedload activity is very high in both shallow and deep sudden flows. These findings can help improve bedload transport models, particularly when using seismic sensors, by providing new insights into bedload dynamics.